PROMICON Asks, AIMEN Answers - Team 'Learning from Nature - Enabling Technologies'

Kicking off the #PromiconAsksPromiconAnswers campaign, we begin with PROMICON's 'Learning from Nature - Enabling Technologies' team, project members from AIMEN have taken the initiative to shed some light on their work. Their objectives include developing advanced methods to quantify microbiomes and phenotypes, optimising conditions for microbiome growth, and understanding functional relationships within microbiomes.

The team’s objectives:

• Quantify Microbiomes and Phenotypes: Develop advanced methods to quantify microbiomes and phenotypes, using techniques like cell sorting, omics profiling, and more.

• Apply Knowledge for Optimisation: Leverage this knowledge to craft optimization strategies, fine-tuning conditions and processes to enhance microbiome performance.

• Derive Understanding of Functional Relationships: Delve into the functional relationships within microbiomes, understanding how components interact and their roles.

AIMEN's primary goal is to create an affordable multispectral sensor for online microbiome culture monitoring, revolutionising the field. The team collects data like temperature, pH, light intensity, Volatile Suspended Solids (VSS), and hyperspectral images during the growth of different microbiomes.

To accurately assess biomass, the researchers employ techniques like VSS, hyperspectral analysis, spectroscopy, artificial vision, and PAM. Understanding single cells is crucial, achieved through artificial vision.

AIMEN collaborates with the rest of the project organisations to develop an online microbiome study tool, using machine learning to enhance prediction accuracy, robustness, and explainability. Optical sensing technology, including spectral, hyperspectral, and multispectral systems, plays a pivotal role in their research.

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